similar to: using innov in arima.sim

Apologies for thickness - I'm sure that this operates as documented and with good reason. However... My understanding of arima.sim() is obviously imperfect. In the example below I assume that x1 and x2 are similar white noise processes with a mean of 5 and a standard deviation of 1. I thought x3 should be an AR1 process but still have a mean of 5 and a sd of 1. Why does x3 have a mean of ~7?

Hi, I am using the arima.sim function to generate some AR time series. However, the function does not seem to produce exactly the same time series when I specify the innov parameter. For example > r <- rnorm(300) > x <- arima.sim(300, model=list(order=c(1,0,0),ar=c(.96)), innov=r, n.start=10) > y <- arima.sim(300, model=list(order=c(1,0,0),ar=c(.96)), innov=r, n.start=10) >

Hi, I have been using arima.sim from the stats package recently, and I'm wondering why I get different results when using what seem to be the same parameters. For example, I've given examples of three different ways to run arima.sim with what I believe are the same parameters. It's my understanding from the R documentation that rnorm is the default function for rand.gen if not

I am trying to simulate time series data for an ar(1) and ma(1) process. I want the error term to have either a t distribution with 1 degree of freedom or a normal distribution with mean=0 and sd=1. Here is my code: error.model=function(n){rnorm(n,mean=0, sd=1)} data<-arima.sim(model=list(ar=c(0.1)), n=1000, n.start=200, start.innov=rnorm(200,mean=0, sd=1), rand.gen=error.model ) data

Hi Everyone, I'm having a problem with arima.sim. Namely specifying inital values for the series. If I generate a random walk > vs = rnorm(100,0,1) > xs = cumsum(vs) and fit an ARIMA(1,0,0) to it > xarima = arima(xs,order=c(1,0,0)) > xarima Call: arima(x = xs, order = c(1, 0, 0)) Coefficients: ar1 intercept 0.9895 8.6341 s.e. 0.0106 6.1869 I should

Hello, I have a question about function arima.sim I tried to somulate a AR(1) process, with no innovation, no error term. I used this code: library(forecast) e=rnorm(100,mean=0,sd=0) series=arima.sim(model=list(ar=0.75),n=100,innov=e)+20 Then I tried to applicate ti this series auto.arima function: mod1<-auto.arima(series,stepwise=FALSE,trace=TRUE,ic='aicc') The best model returned

Hi, Following convention below: y(t) = Ax(t)+Bu(t)+eps(t) # observation eq x(t) = Cx(t-1)+Du(t)+eta(t) # state eq I modified the following routine (which I copied from: http://www.stat.pitt.edu/stoffer/tsa2/Rcode/Kall.R) to accommodate u(t), an exogenous input to the system. for (i in 2:N){ xp[[i]]=C%*%xf[[i-1]] Pp[[i]]=C%*%Pf[[i-1]]%*%t(C)+Q siginv=A[[i]]%*%Pp[[i]]%*%t(A[[i]])+R

hi, I am using speex1.2beta2 on a TI 54x on narrow band I have been trying to get speex to work for a while now, and it's been a real teeter-totter ride. For a long time I noticed that I will get a project to work and then without changing any code and programming it to an eprom/flash the project will not work. It turns out it was a value called innov_save. I found this bugger by zero

Hi, I would like to make a replication of 10 of a linear, first order Autoregressive function, with respect to the replication of its innovation, e. for example: #where e is a random variables of innovation (from GEV distribution-that explains the rgev) #by using the arima.sim model from TSA package, I try to produce Y replicates, with respect to every replicates of e, #means for e[,1], I want

Dear useRs, I want to simulate a time series (stationary; the distribution of values is skewed to the right; quite a few ARMA absolute standardized residuals above 2 - about 8% of them). Is this the right way to do it? #-------------------------------- load("rdtb") #the time series > summary(rdtb) Min. 1st Qu. Median Mean 3rd Qu. Max. -1.11800 -0.65010 -0.09091

Hello, when I work in R, I write code in a text file that I run with the "source(filename)" command. In R2.1.1 the file is read-only while the source command is executed. This was not the case in R2.0.1. Is this a bug-fix or is it possible not to have the file read-only when executed? Best regards Vidar

I noticed that in the narrow band and wide band destroy functions only the main pointer is being freed. I think that it should be: void nb_decoder_destroy(void *state) { DecState *st; st=(DecState*)state; speex_free (st->inBuf); speex_free (st->excBuf); speex_free (st->innov); speex_free (st->interp_qlpc); speex_free (st->qlsp); speex_free

I am trying to implement a relatively high number of encoders (24/32) on a single DSP and would like to minimize the memory requirements. Has anyone optimized the persistent EncState memory allocation for multiple channels. The default C64x fixed point implementation allocates 5280 bytes of persistent memory per encoder. I'm willing to restrict my settings to complexity 1, quality 3. It

Hello, there seems to be a bug in tapply or barplot in R 1.9.0 that was not in = earlier versions. The following code creates two nice barplots in 1.7.0, = but the first one is bad in 1.9.0: par(mfrow=3Dc(1,2)) x <- rep(1:10,10) y <- runif(100,1,100) z <- tapply(y,x,mean) barplot(z) barplot(as.numeric(z)) although is.numeric(z) returns TRUE! Best regards, Vidar Hjellvik Institute of

Hi This is my first post to this group, so apologies in advance if I get it wrong. I would like to know how the prediction for arima models works in R. I have a time series to which I fit an arima model, of varying AR and MA orders. I then use the predict function to project it forward. I have also written my own function to perform the prediction, but it gives different answers to Arima.predict

Hello! I installed the fSeries package to get some farima time-series which i tried with farimaSim, but unfortunately i got always an error. I tried it this way: > farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1), method="freq") Error in farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1), : ... used in an incorrect context Some ideas? Regards, ___

Good morning everyone, I use for the first time the package fSeries and i try to run the example given by Diethelm Würtz. But when i run its example which is the following # # Example: # Model a GARCH time series process # # Description: # PART I: Estimate GARCH models of the following type ARCH(2) # and GARCH(1,1) with normal conditional distribution functions. # PART II: Simulate

When updating the speex sources from svn tree, I found that the following revision has corrupted the deallocation (segmentation fault): ------------------------------------------------------------------------ r9320 | jm | 2005-05-27 15:05:05 -0300 (Fri, 27 May 2005) | 2 lines Proper de-allocation When compiling with the 9316, everything works fine. but when I update with later

i am using sarima() function as below ___________________________________________________________________________________________ sarima=function(data,p,d,q,P=0,D=0,Q=0,S=-1,tol=.001){ n=length(data) constant=1:n xmean=matrix(1,n,1) if (d>0 & D>0) fitit=arima(data, order=c(p,d,q), seasonal=list(order=c(P,D,Q), period=S),

Full_Name: Vidar Hjellvik Version: 2.0.1 OS: windows Submission from: (NULL) (82.134.28.194) I have an tcltk application that runs without problems in R1.9.1, but when I press the "run"-button (and other buttons as well) in R2.0.1, I get the message: "Error in function () : can't change value of a locked binding". I have another tcltk application that runs fine on